DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Lee, Sung-Yun | - |
dc.contributor.advisor | Choi, U-Jin | - |
dc.contributor.advisor | 이성연 | - |
dc.contributor.advisor | 최우진 | - |
dc.contributor.author | Chang, Wu-Jin | - |
dc.contributor.author | 장우진 | - |
dc.date.accessioned | 2011-12-14T04:53:50Z | - |
dc.date.available | 2011-12-14T04:53:50Z | - |
dc.date.issued | 2001 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=166242&flag=dissertation | - |
dc.identifier.uri | http://hdl.handle.net/10203/42024 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 수학전공, 2001.2, [ vi, 23 p. ] | - |
dc.description.abstract | In viewing stock price process mathematically we need a model. The commonest mathematical model for stock price process is nonlinear stochastic Volterra integral equation. But differently from the linear case, nonlinear stochastic integral equations have few chances to obtain exact solutions. Hence for application it is general that prediction is made by approximating through numerical methods such as binomial scheme, finite difference method, Euler type iteration, Monte Carlo simulation, etc. In this thesis, we obtained the higher rate of convergence than the classical Euler type iteration method by linear prediction using statistical interpolation method. | eng |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | stochastic | - |
dc.subject | 주가 변동과정 | - |
dc.title | (A) statistical linear prediction in stock price process | - |
dc.title.alternative | 주가 변동과정에 있어서 통계적 선형예측 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 166242/325007 | - |
dc.description.department | 한국과학기술원 : 수학전공, | - |
dc.identifier.uid | 000993467 | - |
dc.contributor.localauthor | Lee, Sung-Yun | - |
dc.contributor.localauthor | Choi, U-Jin | - |
dc.contributor.localauthor | 이성연 | - |
dc.contributor.localauthor | 최우진 | - |
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